Journal of Behavioral Medicine, Vol. 22 , No. 4 , 1999
Optimism and Adaptation to Multiple Sclerosis:
What Does Optimism Mean?
Marijda Fournier,1 ,2 Denise de Ridder, 1 and Jozien Bensing1
Accepted for publication: February 8 , 1999
The aim of the present study was to determine the meaning of optimism by explicating the dimensions underlying the notion and their links to adjusting
to MS. Seventy-three patients responded to optimism questionnaire s (i.e.,
the LOT, Generalized Self-Ef® cacy Scale) and outcome questionnaires. In
con® rmatory factor analyses, the underlying dimensions of optimism were
speci® ed. Explanatory structural equation modeling was used to examine
the relation of the dimensions of optimism to coping (CISS), depression
(BDI), and impaired mobility range (SIP). Optimism was found to consist
of three dimensions, namely, outcome expectancies, ef® cacy expectancies, and
unrealistic thinking. Outcome and ef® cacy expectancies explained depression
via emotion-oriented coping but did not explain impaired mobility range either
directly or indirectly. Unrealistic thinking directly explained impaired mobility
range. The present study can be seen as a ® rst step in explicating the role of
optimism in the management of chronic disease.
KEY WORDS: optimism; multiple sclerosis; adaptation.
INTRODUCTION
Multiple sclerosis (MS) is a serious autoimmune disease characterized by
its unpredictable and variable course. MS produces varying degrees of neurological symptom s, cognitive problems, fatigue, and pain (Paty and Poser, 1984;
Sibley, 1990). Given only limited possibilities for in¯ uencing the course and
1 Department
of Health Psychology, Utrecht University, P.O. Box 80140 , 3508 TC Utrecht, The
Netherlands.
2 To whom correspondence should be addressed. e-mail: M.Fournier@f ss.uu.nl.
303
0160-7715 / 99 / 0800-0303$16.00
/0 Ó
1999 Plenum Publishing Corporation
304
Fournier, de Ridder, and Bensing
symptoms of MS (Scheinberg, 1994), patients must learn to live with the uncertainty of the disease’ s progression, their symptoms, and the psychosocial consequences (Eklund and MacDonald, 1991). Activities of daily living are disrupted,
including interpersonal, vocational, sexual, and family functioning (Eklund and
MacDonald, 1991; Murray, 1995). The repeatedly adjustments, the inability to
walk, the fatigue, and the uncertainty about the future are the most frustrating
aspects of the disease (Buelow, 1991; Murray, 1995). Although some patients
successfully manage these problems, satisfactory adaptation is not reserved for
all patients, as can be seen from the prevalence of depression, which ranges from
27 to 54% (Minden and Schiffer, 1990). Although several studies have shown
a signi® cant relation between physical symptoms and adaptation (Rudick et al.,
1992; Zeldow and Pavlou, 1984), physical symptoms alone do not explain differences in psychological functioning (McIvor et al., 1984; Walsh and Walsh,
1987). Adapting to MS also depends on coping skills (Aikens et al., 1997;
Brooks and Matson, 1982; Buelow, 1991; Eklund and MacDonald, 1991; Warren et al., 1991), appraisal of one’ s symptoms (Wineman et al., 1994), and the
personal and social resources available to the patient (Shnek et al., 1995; Stuifbergen and Rogers, 1997; Wassem, 1992; for review, see Murray, 1995).
The personal resource of optimism has been shown to play both a direct
role and an indirect role (via coping by means of engagement) in the adaptation
to such acute medical stressors as coronary bypass graft surgery (Fitzgerald et
al., 1993; Scheier et al., 1989), early breast cancer surgery (Carver et al., 1994,
1993), and rheumatoid arthritis (Brenner et al., 1994; Holman and Lorig, 1992),
in the sense of improved well-being and fewer physical symptoms. Although
the de® nition of optim ism seems quite obvious, examination of the literature
reveals several different de® nitions: dispositional optim ism (Scheier and Carver,
1985), generalized self-ef® cacy (Schwarzer, 1993; Bandura, 1988), optimistic
explanatory style (Seligman, 1991), unrealistic optimism (Weinstein, 1980; Taylor, 1989), and defensive pessimism (Cantor and Norem, 1989). The purpose of
the present study is to determine the relations between these de® nitions of optimism, along with their relation to the adaptation of patients with MS.
As can be seen, moreover, the de® nitions of optim ism pertain to different
aspects of optim ism. Dispositional optimism is ª the tendency to believe that one
will generally experience good outcom es in lifeº (Scheier and Carver, 1985)
and is based on the behavioral self-regulation theory of Carver and Scheier
(1981). Generalized self-ef® cacy is ª global con® dence in one’ s coping ability
across a wide range of demanding situationsº (Schwarzer, 1994) and is based
on the social learning theory of Bandura (1986). Optimistic explanatory style,
the reverse of the depressive attributional style, pertains to one’ s tendency habitually to explain uncontrollabl e negative events by causes that are unstable, speci® c, and external and to explain positive events by causes that are permanent,
general, and internal (Seligman, 1991; Peterson and De Avila, 1995). Unrealis-
Optimism and Adaptation to Multiple Sclerosis
305
tic optimism pertains to ª the underestimation of the likelihood of experiencing
negative events and the belief that positive events are more likely to happen to
the self than to othersº (Weinstein, 1980), and Taylor (1989) considers unrealistic optimism to be a kind of positive illusion. Defensive pessimism pertains
to ª a cognitive strategy that involves setting low expectations and ruminating
about or `playing through’ possible outcomes, even if the problems in the past
have always been managedº (Cantor and Norem, 1989; Norem and Crandall,
1991). Although defensive pessimists tend to have low expectations and moderate levels of anxiety prior to a stressful event, they nevertheless confront the
situation and prepare extensively for possible negative events, which is in contrast to a pessimistic tendency to withdraw and avoid negative events. Optimists
have positive expectations but the same coping manner as defensive pessimists
(Showers and Ruben, 1990).
Some speci® c claims about the associations between the de® nitions of optimism have been made in the research literature. Schwarzer (1994) distinguishes
functional versus defensive optimism and suggests that the two can be expected to
negatively relate. Dispositional optimism , optim istic explanatory style, and generalized self-ef® cacy are classi® ed as functional optim ism because of their relations to effective health behaviors. Unrealistic optimism is classi® ed as defensive optimism because of its presumably underm ining effects on taking precautions, counteracting effective health behaviors. Both Schwarzer (1994) and Carver
and Scheier (1981, 1994) distinguish outcom e versus ef® cacy expectancies, while
Wallston (1994) distinguishes cautious optim ism (comparable to defensive pessimism) versus cockeyed optim ism (comparable to unrealistic optimism ).
Evidence in favor of one set of relations over another does not exist because,
in most studies, only two de® nitions of optim ism have been employed (i.e.,
Hjelle et al., 1996; Hull and Mendolia, 1991; Hummer et al., 1992; Peterson
and De Avila, 1995; Scheier and Carver, 1992; Schiaf® no and Revenson, 1992;
Schwarzer, 1993; Shnek et al., 1995). The purpose of the present study is therefore to determine whether the ® ve de® nitions of optimism identi® ed in the literature represent a single underlying dimension, namely, optimism, or whether they
represent an assembly of distinct dimensions of the same notion. The results are
further validated by exploring the role of optim ism in relation to coping, depression, and impairment in physical mobility among MS patients.
METHOD
Participants
Of the 100 MS patients recruited via a patients’ organization, 75 patients
responded to the questionnaires mailed to them. Patients who did not answer
306
Fournier, de Ridder, and Bensing
three or more of the questionnaire s were excluded from the analyses, which
produced a total of 73 patients (17 male and 56 female). The mean age of the
patients was 45.0 years (SD = 9.9 years). Most of the patients had a partner
(75% ) and children (63%). The educational levels varied with no speci® c level
overrepresented. Of the 73 patients, 19% had a job. The reason mentioned by
most of the participants for not working was being unable to work, and they
received disability insurance. The mean time since diagnosis was 9.3 years (SD
= 6.5 years; range = 1±38 years). Of the 73 patients, 31% experienced ¯ uctuating or worsening symptom s in the month prior to the research and 69%
experienced no changes in their MS symptoms in the month prior. By means
of a self-report checklist, patients reported their actual complaints. In general,
the present sample could be identi® ed as moderately invalid: 84% of the total
sample reported fatigue; 77% reported limited walking ability, and 16% was
paralyzed; 53% reported sensitivity problems; 38% reported incontinence , and
40% bowel problem s; 33% reported concentration problem s, and 30% reported
memory problems; 18% reported speech problem s; and 22 and 30%, respectively, reported ambiguous symptoms, indicating dizziness and sleep problems.
The occurrence of more than 6 of these 11 symptoms was reported in 16% of
the patients, which could suggest that these patients were in an active phase of
MS while completing the questionnaires.
Measures of Optimism
Dispositional Optimism. This was measured with the Life Orientation Test
(LOT) (Scheier and Carver, 1985), which consists of eight items plus four ® ller
items. Of the eight items, four are stated positively and four are stated negatively. The subjects are asked to indicate their agreement with the items on a
5-point Likert scale ranging from strongly disagree (0) to strongly agree (4).
In line with Marshall et al. (1992), who showed that the items from the LOT
represent more or less two independent dimensions, separate scores were calculated for dispositional optimism and pessimism. Principal-component analyses
with varimax rotation indeed revealed such a component structure (eigenvalues,
2.45 and 2.44; explained variance, 61.1% ), although one positively stated item
(item 11) loaded on both components. The LOT has been shown to be internally
consistent for both populations with and without disease and appeared to have
predictive and discriminant validity (Scheier et al., 1994). Cronbach’ s a for the
present sample was found to be .80 for the total scale; Cronbach’ s a ’ s for the
optimism and pessimism scales separately were .72 and .77, respectively.
Generalized Self-Ef® cacy. This was measured with the Generalized SelfEf® cacy Scale (Schwarzer and Jerusalem, 1989), which contains 10 items. A
higher total score re¯ ects an optimistic appraisal of one’ s capabilities and more
Optimism and Adaptation to Multiple Sclerosis
307
con® dence in one’ s coping capacity. Research has shown the Generalized SelfEf® cacy Scale to be an internally consistent and valid instrument (Schwarzer,
1993). Cronbach’ s a in the present study was .87.
Explanatory Style. This was measured with the Forced-Choice Attributional Style Questionnaire (Forced-Choice ASQ), consisting of 48 items (Reivich
and Seligman, 1991). The scale contains 24 positive and 24 negative events and
must be answered by choosing the most likely cause from two ® xed alternatives.
The scores are derived by assigning a value of 1 to the internal, stable, and global
responses (optimistic explanatory style) and a value of 0 to the external, unstable, and speci® c responses (pessimistic explanatory style) (Reivich, 1995). Three
items (Nos. 12, 37, and 42) were changed because their content refers to being
healthy, which is simply not applicable in cases of MS. For example, item 12,
ª You were extremely healthy all year,º was replaced by ª You were free of complaint all year.º The Forced-Choice ASQ was not used in the analyses, due to
the low internal consistency of the scores for both optimism and pessimism;
Cronbach’ s a ’ s were .43 and .18 for the two dimensions. The internal consistency for the underlying dimensions (internal / external, permanent / unstable,
global / speci® c) was even worse. A possible explanation for these outcom es is
the answering format, as the ® xed alternatives often did not characterize one’ s
interpretation of the situation, which was re¯ ected in the high nonresponse (n =
63). Reivich (1995) found similar reactions in healthy respondents.
Unrealistic Optimism. This was measured using Comparative Risk Judgement Rating Forms (Weinstein, 1980; Otten, 1995). In response to 20 items
concerning several illness-speci® c situations, patients are asked to judge their
chances of experiencing them compared to the average person of the same age,
gender, and form of illness. The possible response options ranged from ± 4 to
4. Unrealistic optimism on the group level was determined by applying Student’ s t test to determine whether the group means for the positive and negative
events differed signi® cantly from zero and, thus, showed patients to believe that
they were more likely to experience positive events and less likely to experience negative events when compared to their peers (Weinstein, 1980). In line
with Hoorens (1996), separate scores were calculated for the positive and negative events. The comparative estimates were con® rmed to be valid for revealing
biases, as can be seen when gay men were asked about AIDS (Taylor et al.,
1991; Weinstein and Klein, 1996). Cronbach’ s a ’ s for the present sample were
found to be internally consistent with .79 and .80, respectively.
Defensive Pessimism. This was measured using a revised version of the
Optimism-Pessimism Prescreening Questionnaire (OPPQ) (Cantor and Norem,
1989; Norem and Crandall, 1991). The original instrum ent was created for academic performance situations and therefore revised to measure rumination about
the chronic illness and its consequences, on the one hand, and recognition that
one can attempt to deal with the illness, on the other hand. After correcting for
308
Fournier, de Ridder, and Bensing
low (negative) item±total correlations (which depress Cronbach’ s a ), ® ve of the
seven items were selected for analysis and found to have a Cronbach’ s a of
.65.
A General Positive Outlook on Life. This was measured using the Optimism & Pessimism Scale (O&P scale) (Dember et al., 1989), which consists of
36 items (18 positive and 18 negative). The 20 ® ller items included in the original instrum ent were omitted in the present study to reduce the time demands for
subjects. The patients are asked to indicate their agreement with the items on a
4-point scale. The third rating category was mistakenly formulated as ª slightly
agreeº rather than ª disagree.º The other formulations were ª strongly agreeº (1),
ª agreeº (2), and ª strongly disagreeº (4). The O&P scale measures several content areas relevant to optimism , including the general outlook on people, the
world, and the future; expectations regarding one’ s own personal situation; processing of current information; and current behavioral choices. The O&P scale
can be seen as a comprehensive measure of optim ism although this is not as
yet theoretically founded. The scale has been shown to be internally consistent
and valid in several studies (Hummer et al., 1992; Dember et al., 1989). In the
present study, Cronbach’ s a ’ s for optim ism and pessimism were found to be .82
and .87, respectively.
Measures of Adaptation
The following instrum ents were used to measure affect, coping, depression,
and psychophysiosoc ial functioning and thereby explore the relation between
optimism and adaptation to Multiple Sclerosis.
Positive and Negative Affect. These were measured with the Positive and
Negative Affectivity Scale (Watson et al., 1988), which consists of 10 positive
and 10 negative words measuring one’ s general feelings. The scale has been
shown to be internally consistent and valid (Watson et al., 1988). In the present
study, both positive affectivity and negative affectivity proved to be internally
consistent, with Cronbach’ s a ’ s of .76 and .86, respectively.
Task-Oriented Coping, Emotion-Oriented Coping, and Avoidance-Oriented
Coping. These were measured with the Coping Inventory for Stressful Situations
(CISS; Endler and Parker, 1994), which consists of 48 items. Coping by altering the situation is re¯ ected by higher scores for task-oriented coping, coping
by regulating emotional distress is re¯ ected by higher scores for emotion-oriented coping, and coping by seeking other people’ s company or distraction is
re¯ ected by higher scores for avoidance-oriented coping. The CISS proved to
be reliable and valid in healthy populations (Cook and Heppner, 1997; Endler
and Parker, 1994), as well as in the medically ill (Sm ari
 and Valtysd
 ottir,
 1997).
In the present study, Cronbach’ s a ’ s were .88, .90, and .87, respectively.
Optimism and Adaptation to Multiple Sclerosis
309
Depressive Symptoms. These were measured with the Beck Depression
Inventory (BDI; Beck et al., 1979; Bouman et al., 1985), which consists of 21
items. The BDI proved to be internally consistent and valid in the medically
ill, even though the overlap in somatic symptoms warrants caution (Beck et al.,
1988). A modi® ed version has recently been formulated to reduce the potential
in¯ uence of MS symptoms on depression screening (Mohr et al., 1997). As the
reliability and correlations with the optimism instruments did not differ for the
original BDI and the revised version in the present study, the original BDI was
used in the analyses. Cronbach’ s a was .87. Scores lower than 9 are viewed as
normal, scores between 10 and 20 are associated with mild levels of depression, scores between 20 and 30 re¯ ect moderate depression, and scores above
30 re¯ ect severe depression (Kendall et al., 1987).
Psychological, Physical, and Social Functioning. This was measured by
the 68-item version of the Sickness Impact Pro® le (SIP; de Bruin et al., 1994).
The SIP contains six scales measuring impairment in somatic autonom y, mobility
control, psychological autonom y and communication, social behavior, emotional
stability, and mobility range. A higher score means greater impairment. The SIP
proved to be internally consistent and valid (Post et al., 1996). Cronbach’ s a ’ s
were .88, .81, .83, .78, .67, and .81, respectively. Given the small sample size,
only the scale measuring impairment in mobility range was used in the analyses.
This scale indicates the in¯ uence of health status on a number of daily tasks (de
Bruin et al., 1994).
Analyses
The aim of the present study was to answer the following questions: What
is the dimensional structure of optim ism? and In the case of a more dimensional
structure of optimism, are the dimensions differentially related to the elements of
adaptation? Expectations with regard to optimism and adaptation were derived
from the model of Lazarus and Folkman (1984) (see Fig. 1 for the hypothesized
adaptation model). Optimism as a coping resource has thought to precede and
in¯ uence coping, which in turn mediates the stress of the chronic illness (Folkman and Lazarus, 1984; Moos and Schaefer, 1982). In the present study, it is
hypothesized that optim ism will be related directly and indirectly, via coping, to
less depression and less impairment of physical mobility.
In order to determine the dimensional structure of optimism , maximumlikelihood con® rmatory factor analysis (LISREL8.12) (Joreskog
and S orbom,
È
È
1993) was applied to the various measures of optim ism. The input was the correlation matrix with the means and standard deviations for the various measures.
In order to test the assumption of normality, the variables were evaluated in terms
310
Fournier, de Ridder, and Bensing
Fig. 1 . Hypothesized adaptation model.
of skewness. The skewness of all variables but the BDI was between ± 1.0 and
+1.0, but the distribution of the BDI was not severely skewed (skewness = 1.25,
SD = .3). Therefore, all variables proved to have a normal distribution.
Three models were speci® ed. In the ® rst model, optim ism is assumed to
represent one construct, which means that the different measures of optimism
refer to the same phenom enon. In the second model, optim ism is assumed to
encompass both a functional and a defensive orientation. This is in accordance
with the model proposed by Schwarzer (1994) to explain the apparent contradiction between optim ism as health effective and optimism as health risk by
failing self-protective behavior. In the third model, the underlying structure of
optimism is assumed to consist of outcom e expectancies, ef® cacy expectancies,
and being unrealistic with respect to one’ s risks and chances (based on Bandura,
1988; Carver and Scheier, 1994; Wallston, 1994). Bandura (1988) evaluates ef® cacy expectancies also in terms of its deviation from the realistic situation and,
thus, in terms of whether or not the beliefs in one’ s capabilities are unrealistically exaggerated. Wallston (1994) does the same for outcome expectancies
and, thus, in terms of whether the expected favorable outcomes are delusional
or realistic. Both Carver and Scheier (1994) and Schwarzer (1994) emphasize
the role of outcom e and ef® cacy expectancies in the determination of behavior
but disagree on exactly what determines what. In the present study this problem
is not discussed.
Finally, the best-® tting model was taken as the starting point for exploring the role of optim ism in adapting to MS. Using structural equation modeling
(LISREL8.12), the role of optimism in explaining the variance in adaptation was
explored. Only latent variables were used in the analyses. Structural equation
Optimism and Adaptation to Multiple Sclerosis
311
modeling has the advantage of adjusting for measurement errors and permits the
inclusion of the resultant latent variables of optimism in the adaptation model.
Starting with the full model, the nonsigni® cant paths between the latent variables
were stepwise removed to obtain the best-® tting and most parsimonious model.
The paths via coping were evaluated ® rst, followed by evaluation of the direct
paths between optimism and adaptation. Each model was evaluated by examining the parameter estimates and measures of overall ® t provided by LISREL
(Joreskog,
1993). 3
È
RESULTS
Level of Optimism
The basic descriptive data, means, and standard deviations for the optim ism
and adaptation scales are presented in Table 1. In the present sample, 35.6% (n
= 26) of the patients reported a mild level of depression, 8.2% (n = 6) reported
moderate depression, and 4.1% (n = 3) reported severe depression. More than
half of the patients reported few depressive symptoms.
Compared to a healthy population, the present sample is characterized by
somewhat less dispositional optim ism [mean = 21.8, SD = 4.8 (Scheier and
Carver, 1985)] and an equal amount of generalized self-ef® cacy [norm score z =
.064, p = .48 (Schwarzer, 1993)]. Unrealistic optimism is indicated by a group
mean that signi® cantly differs from zero (Weinstein, 1980), and the present sample is not signi® cantly unrealistic optimistic with regard to positive events [t =
1.897 (df = 72), p = .062] and was signi® cantly unrealistic optimistic with regard
to negative events [t = 7.906 (df = 72), p = .000]. More patients were unrealistically optim istic about negative events (71.2%; n = 52) than about positive
events (48.0% ; n = 35). As no signi® cant differences were found between the
male and the female patients on the several optimism scales, the results were
not analyzed separately for males and females.
3 Several
measures indicate the ® t of the model, four of which are applied in the present study. ( 1 )
Chi-square indicates the discrepancy between the covariance matrix predicted by the model and
the observed covariance matrix; a signi® cant discrepancy ( p value) results in model rejection. ( 2 )
Critical N (CN) indicates the minimum sample size for which the value of chi-square would be
signi® cant, which is relevant for small sample sizes. The criterion of CN is 200 and above (Bollen
and Liang, 1988 ). ( 3 ) Root mean square of approximation (RMSEA) indicates the ® t of the model
taking the parsimony into account; a value of . 05 or lower means a close ® t, while a value of up
to .08 indicates a reasonable ® t (Joreskog
and Sorbom,
1993 ). (4 ) Adjusted goodness-of-® t index
È
È
(AGFI) measures how much better the model ® ts compared to no model at all. The AGFI should
be above . 92 . To indicate the best optimism model, we compared the differences in the chi-square
values for the models, controlling for degrees of freedom (Browne and Cudeck, 1993 ).
Fournier, de Ridder, and Bensing
312
Table I. Means, Standard Deviations, and Scale Ranges for the Optimism and Adaptation
Measures
Instrument
Life Orientation Test
Optimism scale
Pessimism scale
Generalized Self-Ef® cacy Scale
Unrealistic optimism for positive events
Unrealistic optimism for negative events
Defensive pessimism
Optimism & Pessimism scale
Optimism scale
Pessimism scale
Positive affectivity
Negative affectivity
CISS
Task-oriented coping
Emotion-ori ented coping
Avoidant-oriented coping
Depression, BDI
SIP
Impairment of Somatic Autonomy
Impairment of Mobility Control
Impairment of Psychological Autonomy / Communication
Impairment of Emotional Stability
Impairment of Social Behavior
Impairment of Mobility Range
Mean
SD
Scale range
20 . 3
9.9
5.6
29 . 6
2.2
9.1
25 . 5
5 .2
2 .8
3 .3
4 .7
9 .8
9 .8
9 .3
0 ±32
0 ±16
0 ±16
10 ±40
40 ±40
40 ±40
5 ±55
46 . 7
31 . 8
33 . 7
21 . 3
7 .9
8 .6
5 .7
7 .3
18 ±72
18 ±72
10 ±50
10 ±50
48 . 4
32 . 4
36 . 9
11 .0
9 .2
8 .9
9 .0
8 .3
16 ±80
16 ±80
16 ±80
0 ±63
3.1
5.9
3 .7
3 .1
0 ±17
0 ±12
3.1
1.3
6.7
3.2
2 .9
1 .4
2 .9
2 .7
0 ±11
0 ±6
0 ±12
0 ±10
±
±
Con® rmatory Factor Analysis of Optimism
As can be seen from Table II, dispositional optim ism and pessimism (LOT)
were related to most of the other measures of optim ism with the exception of
generalized self-ef® cacy and unrealistic optimism for negative events. The latter
scales were barely associated with any of the other scales, which suggests that
they may relate to other dimensions of optim ism. While the O&P scale (Dember
et al., 1989) was related to most of the other optimism scales, it appears that
the scale measures several aspects of optim ism without distinguishing between
them. As the purpose of the present study was to clarify the relations between
the various aspects of optimism , the O&P scale was not used in further analyses.
Three models of the dimensional structure of optimism were next tested
using LISREL8.12. Based on the literature, whether optim ism represents one
factor (optim ism), two factors (functional and defensive), or three factors (outcome expectancies, ef® cacy expectancies, and unrealistic thinking) was tested.
In Table III, the goodness-of- ® t indices for the three alternative models are presented.
Optimism and Adaptation to Multiple Sclerosis
313
Table II. Correlation Matrix for the Optimism Measures (n
= 73 )
Unrealistic
optimism
LOT
opt.
LOT
Optimism
Pessimism
Generalized selfef® cacy
Defensive pessimism
Unrealistic optimism
Positive events
Negative events
O&P-scale
Optimism
Pessimism
LOT
pess.
General
ef® cacy
Defens.
pess.
Positive
Negative
O&P
optimism
± .442 ***
± . 026
± .351**
± . 056
.214
± . 106
.351 **
.063
.126
± .409 ***
± . 109
± . 002
± .200
. 543 ***
± .410 ***
± .170
± . 411***
. 681 ***
± .103
. 458 ***
± .110
.212
.221
.348 **
± .377***
.036
± .122
± .295 *
< . 05 .
< .01 .
*** p < . 001 .
*p
** p
As can be seen, the one-factor model did not ® t the data, which suggests
that optim ism is not represented by a single underlying construct (see also Fig.
2). The two-factor model yielded satisfactory values of the ® t measures, which
suggests that optimism may be represented by a functional and defensive orientation (see Fig. 3). In accordance with Schwarzer (1994), dispositional optim ism
and generalized self-ef® cacy were classi® ed as functional while unrealistic optimism was classi® ed as defensive. Defensive pessimism (OPPQ-R) was somewhat related to both orientations, because it includes both a realistic (opposite
to defensive) orientation and a functional orientation (outcom e expectancies).
Although the two-factor model seemed suitable, the Generalized Self-Ef® cacy
scale did not account for any variance of the functional orientation ( k = .01, t =
.10). This suggests that self-ef® cacy may constitute a separate element of optimism and that a three-factor model of the dimensional structure of optim ism
may be more appropriate.
The three-factor model indeed yielded a good ® t. Each of the optim ism
Table III. Goodness-of-F it Measures for Three Models of Optimism
v
Model 1 : one latent variable
Model 2 : two latent variables
Model 3 : three latent variables
2
190 .9
7 .9
3 .7
df
p value
Critical N
RMSEA
AGFI
11
9
7
.00
.54
.82
10 .33
198 .02
363 .18
. 477
.0
.0
± .066
.916
.953
314
Fournier, de Ridder, and Bensing
Fig. 2 . One-factor model of optimism.
scales explained a component of optimism (see Fig. 4). Defensive pessimism
was theoretically related to both outcom e expectancy and unrealistic thinking,
although in the present study its relation to unrealistic thinking was apparent only
when its relation to outcom e expectancies was omitted ( k = ± .27, t = ± 2 .1). As
the model including both relations showed the best ® t, it is assumed that defensive pessimism relates to both outcom e expectancies and unrealistic thinking.
Optimism and Adaptation to Multiple Sclerosis
315
Fig. 3 . Two-factor model of optimism.
In conclusion, the model assuming three latent dimensions of optim ism
showed the best ® t. Moving from one to two factors improved the v 2 value by
183.0 (df = 2, p < .001). When moving from two to three factors, the v 2 value
did not improve signi® cantly (v 2 = 4.2, df = 2, p = .13). As the role of generalized self-ef® cacy was completely absent in the two-factor model, however,
316
Fournier, de Ridder, and Bensing
Fig. 4 . Three-factor model of optimism.
its inclusion in the three-factor model produced a more complete and better-® tting model of optimism . Optimism thus appears to consist of three dimensions,
namely, outcom e expectancies, ef® cacy expectancies, and unrealistic thinking,
although outcom e expectancies and unrealistic thinking partly overlap (r 2 = .40,
t = 3.14). In the following, the validity of the three-factor model is further examined by exploring the relations of the various dimensions of optim ism to the
adaptation of patients to MS.
Optimism and Adaptation to Multiple Sclerosis
317
Table IV. Correlation Matrix for the Optimism and Adaptation Measures (n
PA
LOT
Optimism
Pessimism
Generalized self-ef® cacy
Defensive pessimism
Unrealistic optimism
Positive events
Negative events
. 23 *
± .13
. 25
± .14
. 25 *
. 07
NA
± .49***
. 41 ***
± . 23 *
.35 **
± . 28 *
± . 15
TCISS
. 12
ECISS
± . 46 ***
.11
. 02
.39 ***
± .27*
. 30 *
. 17
± .25*
± .06
± .09
± .27*
= 73 )a
ACISS
BDI
. 16
± . 53 ***
. 22
. 06
.46 ***
± .12
.35 **
. 23
± . 47 ***
± .22
± .28*
± . 40 ***
IMR
± . 09
.06
± . 06
.06
± .42***
.00
a PA,
positive affectivity scale; NA, negative affectivity scale; TCISS, task-oriented coping (Coping
Inventory for Stressful Situations); ECISS, emotion-orient ed coping (CISS); ACISS, avoidance
coping (CISS); BDI, Beck Depression Inventory; IMR, Impaired Mobility Range (SIP).
* p < . 05 .
** p < .01 .
*** p < . 001 .
Structural Equation Modeling of Optimism and Adaptation to MS
In Table IV, it can be seen that the optimism and pessimism scales relate
mainly to negative affectivity (NA), emotion-oriented coping (ECISS), and
depression (BDI). The SIP scale measuring impaired mobility range was found
to be most strongly associated with optim ism, even though it was only with
unrealistic optimism for positive events. Given the small sample size in our
study and the signi® cant relations of emotion-oriented coping (ECISS), depression (BDI), and impairment in mobility range (SIP) to the measures of optimism, only emotion-oriented coping, depression, and impaired mobility range
were included in the structural model. Although negative affectivity was also
signi® cantly related to the optim ism scales, its inclusion would make the model
too complex, decreasing its power.
The structural model showed outcom e expectancies, ef® cacy expectancies,
and unrealistic thinking to relate differentially to the latent constructs of emotionoriented coping, depression, and impaired mobility (see Fig. 5).
Outcome expectancies explained depression directly and indirectly via
emotion-oriented coping. Ef® cacy expectancies explained depression indirectly
via emotion oriented coping (but not directly). Both outcom e and ef® cacy expectancies did not explain impaired mobility either directly or indirectly. Unrealistic thinking directly (but not indirectly) explained impaired mobility and
depression. The direct relations of outcome expectancies and unrealistic thinking to depression were signi® cant only in the case of omitting the other. Both
relations were included in the model, as this model provided a better ® t for the
data.
As impaired mobility range contains an objective and subjective element,
318
Fournier, de Ridder, and Bensing
Fig. 5 . Model of optimism and adaptation.
we controlled for the objective limited walking ability (dichotom ous variable:
yes / no) to ® gure out whether the relation of unrealistic thinking to impaired
mobility range was limited by the practical situation. Finding that impaired
mobility range was not signi® cantly explained by the objective limited walking ability in addition to unrealistic thinking (c = ± .30, t = ± .1 .15, v 2 change
= 1.14, p = .8), the objective limited walking ability was not included in the
model.
The preceding model shows different aspects of optimism to play different
roles in adaptation to MS. The model ® t the data moderately but the relatively
low critical N may preclude generalization to large populations (v 2 = 24.4, df =
24, p = .437; RMSEA = .016, AGFI = .89, CN = 127.7).
Optimism and Adaptation to Multiple Sclerosis
319
DISCUSSION
In the present study, a number of theoretically motivated dimensions of optimism were distinguished. The exact structure of the underlying dimensions was
then explored, along with how the various dimensions relate to the adaptation
of patients to MS.
Optimism appears to consist of three dimensions, namely, outcome expectancies, ef® cacy expectancies, and unrealistic thinking, with outcome
expectancies and unrealistic thinking partly overlapping. These dimensions were
differently related to the elements of adaptation, which further validate the threedimensional model of optimism.
There are, nevertheless, a few caveats associated with this distinction. First,
the optim ism scales used here re¯ ected largely the same dimensions of the
model, which means that the ® ndings of the same distinct components could
be spurious. Also, the scales measuring unrealistic optimism for negative events
and defensive pessimism were only weakly re¯ ected in the model, pertaining
to their rather high measurement errors in the model. Nevertheless, the present
model indicates the multifaceted nature of optimism and the fact that the different de® nitions of optim ism encountered in the literature may re¯ ect different
phenomena.
Second, the small sample size in the present sample may, in general, lower
the power of LISREL analyses. However, the power in the present analyses was
suf® cient following recommendations (Boomsma, 1983) and using a constricted
number of variables. As the distribution satis® ed the assumption of normality, it
is unlikely that it has threatened the validity of the results. In addition, the present
sample may not be representative of the referent population. There was a relatively high proportion of female participants in the present study (3 .3 : 1) compared to the more general Dutch MS population (3.0 : 1 to 1 .6 : 1) (Zwanikken,
1997); those MS patients who participate in research are more often disabled
from work and generally have higher incomes than those who do not participate
(Schwartz and Fox, 1995); the recruitment of participants via a patient organization may mean a biased representation of optim ism. Nevertheless, the results
of the present study applies in any case to a speci® c part of the MS population.
Third, the proportion of patients with cognitive impairment was relatively
low (30%) compared to the reported 40% to 70% in MS patients in general (Rao
et al., 1991a; Beatty et al., 1995). The present sample could have a relatively better cognitive state than the general population, or the patients could be unaware
of their cognitive de® cits (Kaplan, 1984; Peyser et al., 1980). It is assumed that
the present ® ndings give an adequate approxim ation of the actual situation, as
Kaplan (1984) found that MS patients are aware of their impaired memory on
a daily basis if they are questioned by means of a checklist, the same method
as used in the present study.
320
Fournier, de Ridder, and Bensing
An additional point of interest is the relation between cognitive impairment
and one’ s overestimation of ADL capabilities (Peyser, 1984) and depression (Rao
et al., 1991b), which may have led to a bias in the reporting of symptoms. On
the other hand, this is argued against by the absence of any relation between
cognitive impairment and depression in general (Good et al., 1992; Krupp et
al., 1994), and the full awareness of depression and distress when patients are
euphoric (Rabins et al., 1986; Surridge, 1969).
Fourth, both optimism and adaptation were measured by self-report, which
makes it dif® cult to determine whether the observed relation between optimism and adaptation is biased by an ª optim isticº rose color interpretation of
adaptation. The signi® cant relations observed between optimism / pessimism and
immunological functioning in other studies (Bandura, 1992; Cohen et al., 1989;
Kamen-Siegel et al., 1991), however, suggest that optimism may establish itself
independently and objectively. In addition, optim ism and adaptation were measured by means of generic instruments, which involves the risk of taking no
notice of the speci® c problem s of MS. On the other hand, generic measures are
accepted measures for studying adaptation in chronic diseases in many studies.
Despite these critical observations, the present study can be seen as a ® rst
step in explaining the meaning of optimism in the management of chronic disease and speci® cally MS. In the present study, the de® nition of optimism appears
to represent outcome expectancies, ef® cacy expectancies, and unrealistic thinking, with outcome expectancies and unrealistic thinking partly overlapping. The
question is whether this model of optimism is independent of the circumstances.
In line with the literature, outcom e and ef® cacy expectancies were expected
to overlap (Carver and Scheier, 1994; Schwarzer, 1994), although the empirical
® ndings tend to be contradictory (i.e., Rabinowitz et al., 1992; Schwarzer, 1993).
The present results may be due to the uncontrollabi lity and unpredictability of the
illness, creating incongruity between one’ s expectations with regard to outcome
and one’ s con® dence in one’ s capabilities. The same reasoning may also apply
to the independence of unrealistic thinking and ef® cacy expectancies.
The partial overlap between outcome expectancies and unrealistic thinking
is in accordance with our expectations based on a study by Tennen and Af¯ eck
(1987), who assumed that expecting positive outcomes for oneself (positive outcome expectancies) combined with an awareness that bad things do happen to
people can produce a tendency to view oneself as less likely than others to
experience bad events (unrealistic positive thinking). The de® nition of unrealistic optim ism by Taylor (1989) also suggests conceptual overlap between outcome expectancies and unrealistic thinking, by referring to unrealistic (outcom e)
expectations for the future. Defensive pessimism was found to consist of both
negative outcom e expectancies and realistic thinking, although the negative outcome expectancies were more central in the model. Unraveling the dimensions
of optim ism also allows us to understand defensive pessimism better.
Optimism and Adaptation to Multiple Sclerosis
321
In spite of their overlap, outcome expectancies and unrealistic thinking
appear to represent different aspects of optimism . Examination of their content
may show positive outcome expectancies to be more related to one’ s hope (Snyder et al., 1991) and unrealistic thinking to be more related to one’ s risk perception (van der Pligt, 1998; Weinstein and Klein, 1996). In conclusion, it appears
that the present model is linked up well with the literature. Nevertheless, a more
sophisticated model is needed to take the illness-dependent circumstances into
account.
To validate further the three-dimensional model of optimism, the relations
of the various dimensions of optimism to emotion-oriented coping, depression,
and impaired mobility range were explored and indeed found to be differentially
related to the elements of adaptation.
In line with the literature (Buelow, 1991; de Ridder et al., 1999; Shnek et
al., 1995), optimism was negatively related to depression in MS. Depending on
the dimension of optimism, however, the impact on depression was mediated by
emotion-oriented coping in the present study. Outcome expectancies related both
directly and indirectly to depression, while ef® cacy expectancies related only
indirectly to depression and unrealistic thinking related only directly to depression.
Given the cross-sectional data, the question of whether emotion-oriented
coping mediates the role of outcom e and ef® cacy expectancies in adaptation to
MS remains to be answered by longitudinal data. The mediating role of coping
was expected, as research shows patients to use emotion-oriented coping most
frequently when diagnosed, in cases of high uncertainty with regard to the illness,
and when the situation is appraised as dangerous (Eklund and MacDonald, 1991;
Murray, 1995; Warren et al., 1991; Wineman et al., 1994). In addition, coping
through acceptance and through the inverse of engagement has been shown to
mediate the impact of outcom e expectancies on depression in diverse populations (i.e., Carver et al., 1993; Scheier et al., 1989). Coping is also assumed to
mediate the relation between ef® cacy expectancies and depression, in the sense
that ef® cacy expectancies encourage the acquisition and practice of useful selfmanagement techniques, which can minimize one’ s vulnerability to stress and
depression (Bandura, 1988; Holman and Lorig, 1992). Useful self-management
techniques in cases of MS are, for example, accepting one’ s disabilities and balancing one’ s rest and activities, which are re¯ ected not in task-oriented coping
but in the absence of emotion-oriented coping.
Unrealistic thinking was found to be directly related to depression in the
present study. In keeping with Taylor and Brown (1988), unrealistic positive
thinking (or unrealistic optimism) may promote happiness and a positive mood
that is not the result of repression or denial (Taylor et al., 1989). In addition,
the link between unrealistic thinking and depression may be conceptual in the
fact that depressives are supposed to be realistic thinkers. However, realistic
Fournier, de Ridder, and Bensing
322
thinking and depression have different implications for behavior. Showers and
Ruben (1990) found defensive pessimism (i.e., partly realistic thinking and partly
negative outcome expectancies in the present study) to be related to nonavoidant
coping and effective preparation for situations, while depression was related to
avoidant coping.
Physical health or impaired mobility range was signi® cantly explained by
unrealistic thinking but not by outcom e or ef® cacy expectancies in the present
study. More speci® cally, unrealistic positive thinking was related to reports of
being able to do more things, which can be explained in two ways. In line with
Taylor and Brown (1988), unrealistic positive thinking (or unrealistic optimism )
may lead to greater persistence, more action, and less fatalism, which can help
patients stay independent and active. Alternatively, unrealistic positive thinking
can be dangerous when it interferes with appropriate precautionary behaviors
(Weinstein and Klein, 1996). MS symptom s can increase as a result of overactivation and exhaustion, which makes too much activity counterproduc tive and
suggests that unrealistic positive thinking can be both adaptive as well as maladaptive.
In conclusion, our exploration of the role of optimism in adaptation to
MS con® rmed the existence of a multidimensional structure. Because of the
exploratory character, it is too early to give conclusions on the consequences for
mental and physical health. Positive outcom e expectancies and positive ef® cacy
expectancies appear to produce better mental health, while the role of unrealistic positive thinking remains unclear. The present results can perhaps be generalized to chronic illness in general, as MS is also characterized by the uncertainty and progressive, disabling course that characterizes other chronic diseases
(Stuifbergen and Rogers, 1997). Future research is, nevertheless, planned to clarify further the role of optimism in the management of chronic illness.
ACKNOWLEDGMENTS
The authors are grateful to Dr. G. H. Maassen, Department of Methodology
and Statistics, Utrecht University, and an expert on LISREL, for his kind help
with the analyses.
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